液冷与智算中心日报｜2026-08-19
追踪液冷技术、AI 智算中心、数据中心能效、学术论文、产品发布、政策标准、投融资与供应链动态的每日中文报告。
1. 今日一句话总结
24小时内，资本继续加码智算中心，但电力、审批与能效约束已前置，液冷和算电协同正转为项目准入项。
从公开信号看，资本并未因为约束而降温，资本开支仍向AI数据中心与液冷环节集中，说明头部厂商和基础设施资本仍在前置锁定园区、容量和交付窗口；但与此同时，扩建继续推进，但电力、选址审批与能源获取仍是主约束，意味着行业竞争的关键变量已不再只是“拿到多少 GPU”，而是“能否把 GPU 放进一个可并网、可散热、可控成本、可持续运行的系统”。技术侧技术侧继续围绕高带宽互连与服务器能效优化，论文侧论文侧继续指向算电协同、液冷优化与能效度量重构，共同指向同一个趋势：单点器件优化的边际价值在下降，网络、供电、储能、液冷和调度软件的系统级协同正在上升为真正的产能约束。对产业链而言，未来更稀缺的不是单一硬件，而是把算力、热管理和能源调度耦合起来的工程交付能力。
学术与产业速览
将论文、视频、产业动态和政策项压缩为可快速扫描的标签；每个标签只保留题目、摘要和来源入口。
学术
论文、研究趋势、学术视频与方法论线索。
Real-Time Control of Sustainable Data Centers: A Two-Layer Model Predicti…
This paper proposes a two-layer model predictive control (MPC) framework for the real-time operation of data centers integrated wit…
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Real-Time Control of Sustainable Data Centers: A Two-Layer Model Predictive Control Framework with Workload Flexibility and Heat Recovery
- 发布时间
- 2026-08-17
- 作者
- Wenyu Liu、Enea Figini、Mario Paolone
- 主题
- 余热回收
摘要
This paper proposes a two-layer model predictive control (MPC) framework for the real-time operation of data centers integrated with on-site photovoltaic generation, battery energy storage, waste heat recovery, and district heating. The upper layer employs scenario-based stochastic optimization to jointly optimize intraday market participation, workload scheduling, and energy management under uncertainty. The lower layer adopts an adaptive tube-based MPC strategy that compensates short-term disturbances while tracking the dispatch references given by the upper layer. The framework further integrates multi-horizon forecasting to support real-time decision making. Microservice-based simulation studies under representative clear-sky and overcast operating conditions demonstrate that the proposed framework accurately tracks dispatch plans despite fast photovoltaic and workload fluctuations. Compared with single-layer control strategies, the adaptive lower-layer controller substantially reduces real-time dispatch deviations and the associated imbalance costs. In addition, the proposed framework naturally adapts to seasonal operating conditions and responds to carbon-aware operating signals, offering a practical approach for economically efficient, sustainable, and grid-supportive operation of future data centers.
中文解读
背景：AI 数据中心负载、功率密度和能源约束同步上升，余热回收、热泵耦合和二次能源利用正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用建模优化、调度分析或算法评估，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向AI 负载波动对电网设备寿命和调频边界的影响。意义：对日报读者而言，它可用于判断数据中心余热能否从成本项转化为能源资产。仍需结合全文实验条件、样本范围和成本假设核验。
参考文献
Wenyu Liu, Enea Figini, Mario Paolone. Real-Time Control of Sustainable Data Centers: A Two-Layer Model Predictive Control Framework with Workload Flexibility and Heat Recovery[J/OL]. (2026-08-17)[2026-08-19]. http://arxiv.org/abs/2608.16432v1.
Machine Learning Guided Cooling System Optimization for Data Center
Effective data
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Machine Learning Guided Cooling System Optimization for Data Center
- 发布时间
- 2026-08-06
- 作者
- Shrenik Jadhav、Zheng Liu
- 主题
- 热管理与液冷
摘要
Effective data
中文解读
背景：AI 数据中心负载、功率密度和能源约束同步上升，液冷、热管理和数据中心能效正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用建模优化、调度分析或算法评估，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向冷却效率、能源利用或运维策略的改进方向。意义：对日报读者而言，它可用于判断液冷方案、热管理路线和高密度部署节奏。仍需结合全文实验条件、样本范围和成本假设核验。
参考文献
Shrenik Jadhav, Zheng Liu. Machine Learning Guided Cooling System Optimization for Data Center[J/OL]. (2026-08-06)[2026-08-19]. https://arxiv.org/abs/2601.02275.
PowerAtlas: Towards Electricity - Computing Co-Scheduling for Power Syste…
The rapid growth of AI workloads is turning data
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PowerAtlas: Towards Electricity - Computing Co-Scheduling for Power Systems
- 发布时间
- 2026-07-29
- 作者
- Kaiwen Jiang、Siya Xu、Ziyue Zhu、Chao Yang、Anh Tuan Luu、Haoran Luo
- 主题
- 算电协同
摘要
The rapid growth of AI workloads is turning data
中文解读
背景：AI 数据中心负载、功率密度和能源约束同步上升，算力负载与电网侧资源的协同调度正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用建模优化、调度分析或算法评估，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向跨地域数据中心负载与电力资源之间的调度关系。意义：对日报读者而言，它可用于判断智算中心建设是否受电网容量、负载波动和调度机制约束。仍需结合全文实验条件、样本范围和成本假设核验。
参考文献
Kaiwen Jiang, Siya Xu, Ziyue Zhu, 等. PowerAtlas: Towards Electricity - Computing Co-Scheduling for Power Systems[J/OL]. (2026-07-29)[2026-08-19]. https://arxiv.org/abs/2607.26710.
Integrating Energy Efficiency into Software Development: Developer Perspe…
In the context of the growing energy
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Integrating Energy Efficiency into Software Development: Developer Perspectives and Requirements
- 发布时间
- 2026-07-24
- 作者
- Anika Hennig、Leonie Schulte、Philipp M. Zähl、Mathias Eggert
- 主题
- 能效优化
摘要
In the context of the growing energy
中文解读
背景：AI 数据中心负载、功率密度和能源约束同步上升，PUE/WUE、能效指标和运营成本控制正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用文献摘要中的模型、实验或案例分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向能效评价口径、运营指标和优化目标的系统化梳理。意义：对日报读者而言，它可用于判断不同能效指标是否真实反映节能和成本收益。仍需结合全文实验条件、样本范围和成本假设核验。
参考文献
Anika Hennig, Leonie Schulte, Philipp M. Zähl, 等. Integrating Energy Efficiency into Software Development: Developer Perspectives and Requirements[J/OL]. (2026-07-24)[2026-08-19]. https://arxiv.org/abs/2607.22168.
InFactPlanner: Planning Sustainable Geo-Distributed LLM Data Centers
The rapid growth of LLM inference is shifting sustainability concerns from one-time training to continuous serving, where infrastru…
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InFactPlanner: Planning Sustainable Geo-Distributed LLM Data Centers
- 发布时间
- 2026-08-13
- 作者
- Nicoletta Tsiopani、Moysis Symeonides、George Pallis、Marios D. Dikaiakos
- 主题
- 热管理与液冷
摘要
The rapid growth of LLM inference is shifting sustainability concerns from one-time training to continuous serving, where infrastructure decisions shape energy
中文解读
背景：AI 数据中心负载、功率密度和能源约束同步上升，液冷、热管理和数据中心能效正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用文献摘要中的模型、实验或案例分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向跨地域数据中心负载与电力资源之间的调度关系。意义：对日报读者而言，它可用于判断液冷方案、热管理路线和高密度部署节奏。仍需结合全文实验条件、样本范围和成本假设核验。
参考文献
Nicoletta Tsiopani, Moysis Symeonides, George Pallis, 等. InFactPlanner: Planning Sustainable Geo-Distributed LLM Data Centers[J/OL]. (2026-08-13)[2026-08-19]. https://arxiv.org/abs/2608.12915.
Techno-Economic Boundary Analysis of Small Modular Reactor Cogeneration f…
Hyperscale data centers are adding firm, high-utilization demand faster than grids can serve it, renewing interest in colocating th…
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Techno-Economic Boundary Analysis of Small Modular Reactor Cogeneration for Hyperscale Data Center IT and Cooling Loads
- 发布时间
- 2026-08-11
- 作者
- Honglin Li、Buxin She、Jie Zhang
- 主题
- 算电协同
摘要
Hyperscale data centers are adding firm, high-utilization demand faster than grids can serve it, renewing interest in colocating them with small modular reactors. Such a plant could earn revenue in two ways, selling low-carbon power and diverting steam to absorption chillers that serve a cooling load accounting for 20-40% of facility electricity use, but neither revenue stream has been priced across the conditions that must coincide. Here we co-optimize reactor dispatch, steam extraction, absorption cooling and grid exchange hourly for a 200 MW$_\mathrm{e}$ data center in the Electric Reliability Council of Texas (ERCOT) region, across 109 runs spanning capital, market, policy, financing and cooling efficiency. At 2023 mid-range reactor capital, the nuclear configurations cost 49-62% more than grid supply even with the Section 45Y production tax credit. The viable region opens near \$5,000 kW$_\mathrm{e}^{-1}$, and nth-of-a-kind capital makes them 77-89% cheaper in 2023, though between parity and 34% more expensive in the low-price 2024 market. A carbon price of \$53-64 tCO$_2^{-1}$ closes the mid-range gap under hourly export crediting. Absorption cooling is dispatched in response to hourly electricity prices and supplies 38% of annual cooling, at an added cost of \$9.2 million yr$^{-1}$ relative to the reactor-only plant; that gap closes at an installed absorption cost of \$60 kW$_\mathrm{c}^{-1}$ at baseline efficiency and \$570 kW$_\mathrm{c}^{-1}$ on a legacy-efficiency campus, against surveyed commercial prices of \$450-1,200 kW$_\mathrm{c}^{-1}$. Together these results delineate the capital, market and policy conditions under which colocated reactor cogeneration is competitive with grid procurement, and the range over which each condition moves the outcome.
中文解读
背景：AI 数据中心负载、功率密度和能源约束同步上升，算力负载与电网侧资源的协同调度正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用综述归纳和指标比较，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向AI 负载波动对电网设备寿命和调频边界的影响。意义：对日报读者而言，它可用于判断智算中心建设是否受电网容量、负载波动和调度机制约束。仍需结合全文实验条件、样本范围和成本假设核验。
参考文献
Honglin Li, Buxin She, Jie Zhang. Techno-Economic Boundary Analysis of Small Modular Reactor Cogeneration for Hyperscale Data Center IT and Cooling Loads[J/OL]. (2026-08-11)[2026-08-19]. http://arxiv.org/abs/2608.10999v1.
PowerScale: Energy -Efficient Geo-Distributed Model Training with Federat…
The power demands of large-scale AI
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PowerScale: Energy -Efficient Geo-Distributed Model Training with Federated Datacenter Power
- 发布时间
- 2026-07-28
- 作者
- Talha Mehboob、Zhe Xu、Michael Zink、David Irwin
- 主题
- 热管理与液冷
摘要
The power demands of large-scale AI
中文解读
背景：AI 数据中心负载、功率密度和能源约束同步上升，液冷、热管理和数据中心能效正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用仿真建模和情景分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向跨地域数据中心负载与电力资源之间的调度关系。意义：对日报读者而言，它可用于判断液冷方案、热管理路线和高密度部署节奏。仍需结合全文实验条件、样本范围和成本假设核验。
参考文献
Talha Mehboob, Zhe Xu, Michael Zink, 等. PowerScale: Energy -Efficient Geo-Distributed Model Training with Federated Datacenter Power[J/OL]. (2026-07-28)[2026-08-19]. https://arxiv.org/abs/2607.25650.
CWind: A Cross-site Router for Large Language Model Inference Serving at …
AI
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CWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms
- 发布时间
- 2026-07-21
- 作者
- Tella Rajashekhar Reddy、Atharva Deshmukh、Liangcheng Yu、Chaojie Zhang、Mike Shepperd、Rohan Gandhi、Anjaly Parayil、Srinivasan Iyengar
- 主题
- 热管理与液冷
摘要
AI
中文解读
背景：AI 数据中心负载、功率密度和能源约束同步上升，液冷、热管理和数据中心能效正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用仿真建模和情景分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向冷却效率、能源利用或运维策略的改进方向。意义：对日报读者而言，它可用于判断液冷方案、热管理路线和高密度部署节奏。仍需结合全文实验条件、样本范围和成本假设核验。
参考文献
Tella Rajashekhar Reddy, Atharva Deshmukh, Liangcheng Yu, 等. CWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms[J/OL]. (2026-07-21)[2026-08-19]. https://arxiv.org/abs/2605.23348.
OldAztec: Big Tech Needs Reliable Nuclear Energy
Sift Stack · 检索词：ACM SIGEnergy data center energy talk。适合作为技术背景或研究趋势补充。
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Patrick Laing, CXO 2.0’s Keynote Speaker, Breaks Down AI Transformation &…
CXO 2.0 Conference · 检索词：AI data center energy conference keynote。适合作为技术背景或研究趋势补充。
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SB Energy co-CEO Rich Hossfeld on Nvidia-backed data center for OpenAI
CNBC Television · 检索词：ACM SIGEnergy data center energy talk。适合作为技术背景或研究趋势补充。
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Solving the Data Centre Energy Crisis | Vittorio Pierangeli, Rolls-Royce …
Data Centre Magazine · 检索词：AI data center energy conference keynote。适合作为技术背景或研究趋势补充。
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The Great Progression, 2025 to 2050, a Full Keynote on an AI & Clean Ener…
Reinvent Futures · 检索词：AI data center energy conference keynote。适合作为技术背景或研究趋势补充。
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WeCan'22: Brainstorming Session with the Audience - Minghua, George, Davi…
Noman Bashir · 检索词：ACM SIGEnergy data center energy talk。适合作为技术背景或研究趋势补充。
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X-energy founder Kam Ghaffarian says AWS and tech titans are targeting sp…
Goal Mint Media · 检索词：ACM SIGEnergy data center energy talk。适合作为技术背景或研究趋势补充。
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智算中心 CapEx/扩建
本期命中 15 条，热度分 51。可作为论文检索、技术路线和后续研究跟踪关键词。
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电力并网与能源约束
本期命中 9 条，热度分 26。可作为论文检索、技术路线和后续研究跟踪关键词。
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AI 芯片供给与交付
本期命中 2 条，热度分 8。可作为论文检索、技术路线和后续研究跟踪关键词。
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产业
产业新闻、技术产品、政策标准、投融资、项目和产业视频。
智算中心/数据中心建设进展：Data Center Dynamics 发布相关报道（原文标题：Application filed for data…
发布时间：2026-08-19；检索窗口内；细节以来源原文为准，本页不复述未核验扩展信息
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电力与能源约束观察：Data Center Dynamics 发布相关报道（原文标题：ABB launches ultracapacitor st…
发布时间：2026-08-19；检索窗口内；细节以来源原文为准，本页不复述未核验扩展信息
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智算中心/数据中心建设进展：Data Center Dynamics 发布相关报道（原文标题：Globalinx buys land in Vir…
发布时间：2026-08-19；检索窗口内；细节以来源原文为准，本页不复述未核验扩展信息
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智算中心/数据中心建设进展：Data Center Dynamics 发布相关报道，涉及 £300（原文标题：DataVita secures £…
发布时间：2026-08-18；检索窗口内；可核验指标：£300；细节以来源原文为准，本页不复述未核验扩展信息
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数据中心产业动态：Data Center Dynamics 发布相关报道，涉及 13GW（原文标题：CBRE: Europe data cente…
发布时间：2026-08-18；检索窗口内；可核验指标：13GW；细节以来源原文为准，本页不复述未核验扩展信息
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数据中心产业动态：Data Center Dynamics 发布相关报道（原文标题：Turkish real estate investment …
发布时间：2026-08-18；检索窗口内；细节以来源原文为准，本页不复述未核验扩展信息
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数据中心产业动态：Data Center Dynamics 发布相关报道（原文标题：Sponsored: AI cooling is no lon…
发布时间：2026-08-18；检索窗口内；细节以来源原文为准，本页不复述未核验扩展信息
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数据中心产业动态：Data Center Dynamics 发布相关报道（原文标题：DayOne partners with Cortical L…
发布时间：2026-08-18；检索窗口内；细节以来源原文为准，本页不复述未核验扩展信息
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电力与能源约束观察：Data Center Knowledge 发布相关报道（原文标题：Data Center Hardware Highligh…
发布时间：2026-08-18；检索窗口内；细节以来源原文为准，本页不复述未核验扩展信息
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AI 算力基础设施动态：HPCwire 发布相关报道，涉及 $700 million（原文标题：What’s Hot Now: Custom AI…
发布时间：2026-08-19；检索窗口内；可核验指标：$700 million；细节以来源原文为准，本页不复述未核验扩展信息
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项目、采购或专利线索：HPCwire 发布相关报道（原文标题：Coherent Begins Customer Sampling of 300mm…
发布时间：2026-08-19；检索窗口内；细节以来源原文为准，本页不复述未核验扩展信息
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Data Center and AI Infrastructure in Arizona: A Knowledge Exchange | Citi…
ASU Energy Forward · 检索词：AI infrastructure datacenter panel discussion。用于补充产业、产品或工程部署观察。
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产业热度指数 10/10
产业热度指数为 10/10：本期自动化检索记录到 19 条候选条目，指数按候选条目数量、来源可信度和栏目覆盖度保守计算。
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4. 最新视频观察
OldAztec: Big Tech Needs Reliable Nuclear Energy
学术讲座 · Sift Stack · 检索词：ACM SIGEnergy data center energy talk
在 YouTube 打开Patrick Laing, CXO 2.0’s Keynote Speaker, Breaks Down AI Transformation & Data Center Myths
学术会议报告 · CXO 2.0 Conference · 检索词：AI data center energy conference keynote
在 YouTube 打开SB Energy co-CEO Rich Hossfeld on Nvidia-backed data center for OpenAI
学术讲座 · CNBC Television · 检索词：ACM SIGEnergy data center energy talk
在 YouTube 打开Solving the Data Centre Energy Crisis | Vittorio Pierangeli, Rolls-Royce at Data Centre LIVE 2026
学术会议报告 · Data Centre Magazine · 检索词：AI data center energy conference keynote
在 YouTube 打开The Great Progression, 2025 to 2050, a Full Keynote on an AI & Clean Energy Future by Peter Leyden
学术会议报告 · Reinvent Futures · 检索词：AI data center energy conference keynote
在 YouTube 打开WeCan'22: Brainstorming Session with the Audience - Minghua, George, David, and Jay
学术讲座 · Noman Bashir · 检索词：ACM SIGEnergy data center energy talk
在 YouTube 打开X-energy founder Kam Ghaffarian says AWS and tech titans are targeting space for future AI data.
学术讲座 · Goal Mint Media · 检索词：ACM SIGEnergy data center energy talk
在 YouTube 打开Data Center and AI Infrastructure in Arizona: A Knowledge Exchange | Cities Panel w/ Paul Westerhoff
专家圆桌 · ASU Energy Forward · 检索词：AI infrastructure datacenter panel discussion
在 YouTube 打开来源链接区
本次检索说明
- 当前自动化环境未配置 Tavily、Bing News 或 SerpAPI 检索密钥；脚本将使用公开 RSS/Atom、公共 arXiv 接口与固定监测源，不会编造产业新闻。
- 公开 RSS/Atom：The Register：未检索到符合条件的高相关条目。
- 公开 RSS/Atom：ServeTheHome：未检索到符合条件的高相关条目。
- 公开 RSS/Atom：NVIDIA Blog：未检索到符合条件的高相关条目。
- 论文池：已从本地论文池读取 25 条候选；池更新时间 2026-08-19 08:07。
- 论文推荐：已启用 latest 模式，优先输出本期候选池中发布时间最新的论文。
- x.ai 论文解读：文本生成失败，已回退到规则化论文摘要；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- x.ai 论文配图：论文 1 生成失败，已使用内置主题图；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- x.ai 论文配图：论文 2 生成失败，已使用内置主题图；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- x.ai 论文配图：论文 3 生成失败，已使用内置主题图；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- x.ai 论文配图：论文 4 生成失败，已使用内置主题图；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- x.ai 论文配图：论文 5 生成失败，已使用内置主题图；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- x.ai 论文配图：论文 6 生成失败，已使用内置主题图；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- x.ai 论文配图：论文 7 生成失败，已使用内置主题图；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- x.ai 论文配图：论文 8 生成失败，已使用内置主题图；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit. To continue making…
- AI 分析：x.ai 调用失败，已回退到规则化模板；原因：HTTP 403：{"code":"permission-denied","error":"Your team 472c8744-ad4f-4879-a588-fa7645e04979 has either used all available credits or reached its monthly spending limit…